| name | symbolic-memory |
| description | Stateless symbolic memory effect for LLM agents using SQL facts + canonical semantics, activated via symbols and JIT meaning (PostgreSQL + Ollama). |
| metadata | {"openclaw":{"emoji":"🧠","homepage":"https://github.com/Th3Hypn0tist/random/blob/main/LLM-symbolic-memory.md","requires":{"bins":["psql","python3"],"env":["PG_DSN","OLLAMA_HOST","OLLAMA_MODEL"],"config":[]}}} |
| user-invocable | true |
| version | 1 |
symbolic-memory
Purpose
Provide a stateless symbolic memory workflow:
- Store facts + canonical semantics in PostgreSQL
- Expose references as symbols
- Activate meaning just-in-time (budgeted)
- Send only activated facts to the LLM (Ollama)
Rule:
Store semantics. Compute meaning. Never confuse the two.
NOTE
This skill does not rely on agent-local persistent memory for long-term state.
Durable knowledge is stored in a shared, versioned symbolic memory substrate
(as defined in the JIT Symbolic Memory design pattern).
The skill may operate without symbolic memory, but long-term coherence
and multi-agent consistency are only guaranteed when it is present.
Design pattern
https://github.com/Th3Hypn0tist/random/blob/main/jit-symbolic-memory-design-pattern
